AIMC Topic: Middle Aged

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Prediction of treatment outcome in burning mouth syndrome patients using machine learning based on clinical data.

Scientific reports
The purpose of this study is to apply a machine learning approach to predict whether patients with burning mouth syndrome (BMS) respond to the initial approach and clonazepam therapy based on clinical data. Among the patients with the primary type of...

The Effect of Applying Robot-Assisted Task-Oriented Training Using Human-Robot Collaborative Interaction Force Control Technology on Upper Limb Function in Stroke Patients: Preliminary Findings.

BioMed research international
Stroke is one of the leading causes of death and the primary cause of acquired disability worldwide. Many stroke survivors have difficulty using their upper limbs, which have important functional roles in the performance of daily life activities. Con...

Robot-assisted Exploration of Somatic Nerves in the Pelvis and Transection of the Sacrospinous Ligament for Alcock Canal Syndrome.

Journal of minimally invasive gynecology
STUDY OBJECTIVE: Some articles have reported the surgical management of Alcock canal syndrome (ACS) using the transperineal [1], transgluteal [2], or conventional laparoscopic approach [3,4]. In 2015, Rey and Oderda [5] reported the first robotic neu...

A Deep Learning Radiomics Model to Identify Poor Outcome in COVID-19 Patients With Underlying Health Conditions: A Multicenter Study.

IEEE journal of biomedical and health informatics
OBJECTIVE: Coronavirus disease 2019 (COVID-19) has caused considerable morbidity and mortality, especially in patients with underlying health conditions. A precise prognostic tool to identify poor outcomes among such cases is desperately needed.

Assessing the Adequacy of Hemodialysis Patients via the Graph-Based Takagi-Sugeno-Kang Fuzzy System.

Computational and mathematical methods in medicine
Maintenance hemodialysis is the main method for the treatment of end-stage renal disease in China. The / value is the gold standard of hemodialysis adequacy. However, / requires repeated blood drawing and evaluation; it is hard to monitor dialysis ad...

A Self-Representation-Based Fuzzy SVM Model for Predicting Vascular Calcification of Hemodialysis Patients.

Computational and mathematical methods in medicine
In end-stage renal disease (ESRD), vascular calcification risk factors are essential for the survival of hemodialysis patients. To effectively assess the level of vascular calcification, the machine learning algorithm can be used to predict the vascu...

Comparison of Supervised Machine Learning Algorithms for Classifying of Home Discharge Possibility in Convalescent Stroke Patients: A Secondary Analysis.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: Classifying the possibility of home discharge is important during stroke rehabilitation to support decision-making. There have been several studies on supervised machine learning algorithms, but only a few have compared the performance of...

Identification of Tissue of Origin and Guided Therapeutic Applications in Cancers of Unknown Primary Using Deep Learning and RNA Sequencing (TransCUPtomics).

The Journal of molecular diagnostics : JMD
Cancers of unknown primary (CUP) are metastatic cancers for which the primary tumor is not found despite thorough diagnostic investigations. Multiple molecular assays have been proposed to identify the tissue of origin (TOO) and inform clinical care;...

A hybrid machine learning/pharmacokinetic approach outperforms maximum a posteriori Bayesian estimation by selectively flattening model priors.

CPT: pharmacometrics & systems pharmacology
Model-informed precision dosing (MIPD) approaches typically apply maximum a posteriori (MAP) Bayesian estimation to determine individual pharmacokinetic (PK) parameters with the goal of optimizing future dosing regimens. This process combines knowled...

Classification of glioblastoma versus primary central nervous system lymphoma using convolutional neural networks.

Scientific reports
A subset of primary central nervous system lymphomas (PCNSL) are difficult to distinguish from glioblastoma multiforme (GBM) on magnetic resonance imaging (MRI). We developed a convolutional neural network (CNN) to distinguish these tumors on contras...